Advertisement

Compliance and Emissions Trading under the Kyoto Protocol: Rules for Uncertain Inventories

Chapter

Abstract

A solution is proposed for proving compliance with emission targets and for emissions trading in the event of uncertainties in reported emission inventories. The solution is based on the undershooting concept, from which the mathematical conditions for both proving compliance with a risk α and calculating effective emissions for trading are derived. Based on the reported emission units, the number of permits granted is reduced in proportion to the uncertainty in the inventory. A country whose inventory has higher uncertainty is thereby allotted fewer permits than a country with the same inventory but smaller uncertainty.

Keywords

greenhouse gas inventory uncertainty compliance with Kyoto Protocol risk of noncompliance undershooting emissions trading effective tradable permits 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Baumol, W. J., & Oates, W. E. (1998). The theory of environmental policy. Cambridge, UK: Cambridge University Press.Google Scholar
  2. Charles, D., Jones, B. M. R., Salway, A. G., Eggleston, H. S., & Milne, R. (1988). Treatment of uncertainties for national estimates of greenhouse gas emissions. Report AEAT-2688-1. Cullham, UK: AEA Technology. See http://www.aeat.co.uk/netcen/airqual/naei/ipcc/uncertainty.Google Scholar
  3. Gawin, R. (2002). Level and trend uncertainties of Kyoto — relevant greenhouse gases in Poland. Interim Report IR-02-045. Laxenburg, Austria: International Institute for Applied Systems Analysis (IIASA).Google Scholar
  4. Gillenwater, M., Sussman, F., & Cohen, J. (2007). Practical applications of uncertainty analysis for national greenhouse gas inventories. (This issue).Google Scholar
  5. Godal, O. (2000). Simulating the carbon permit market with imperfect observations of emissions: Approaching equilibrium through sequential bilateral trade. Interim Report IR-00-060. Laxenburg, Austria: International Institute for Applied Systems Analysis (IIASA).Google Scholar
  6. Godal, O., Ermolev, Y., Klaassen, G., & Obersteiner, M. (2003). Carbon trading with imperfectly observable emissions. Environmental and Resource Economics, 25, 151–169.CrossRefGoogle Scholar
  7. Godal, O., & Klaassen, G. (2003). Compliance and imperfect intertemporal carbon trading. Working Papers in Economics No. 09/03. Bergen, Norway: Department of Economics, University of Bergen.Google Scholar
  8. Gugele, B., Huttunen, K., & Ritter, M. (2005). Annual european community greenhouse gas inventory 1990–2003 and inventory report 2005. Technical Report No. 4/2005. Copenhagen, Denmark: European Environment Agency. http://reports.eea.europa.eu/technical_report_2005_4/en.Google Scholar
  9. Gupta, J., Oltshoorn, X., & Rotenberg, E. (2003). The role of scientific uncertainty in compliance with the Kyoto protocol to the climate change convention. Environmental Science & Policy, 6, 475–486.CrossRefGoogle Scholar
  10. Horabik, J., & Nahorski, Z. (2004). Performance of the carbon market when accounting for uncertainties in GHG inventories. Proceedings of the workshop uncertainty in greenhouse gas inventories: Verification, compliance & trading (pp. 126–134). Warsaw, Poland: SRI PAS & IIASA. http://www.ibspan.waw.pl/GHGUncert2004/papers/Horabik.pdf.Google Scholar
  11. Hung, W., & Wu, J. (2001). A note on the correlation of fuzzy numbers by expected interval. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 9, 517–523.Google Scholar
  12. Jonas, M., Nilsson, S., Bun, R., Dachuk, V., Gusti, M., Horabik, J., et al. (2004a). Preparatory signal detection for Annex I countries under the Kyoto protocol — A lesson for the post-Kyoto policy process. Interim Report IR-04-024. Laxenburg, Austria: International Institute for Applied Systems Analysis (IIASA).Google Scholar
  13. Jonas, M., Nilsson, S., Bun, R., Dachuk, V., Gusti, M., Horabik, J., et al. (2004b). Preparatory signal detection for Annex I countries under the Kyoto protocol-Advanced monitoring including uncertainty. Interim Report IR-04-029. Laxenburg, Austria: International Institute for Applied Systems Analysis (IIASA).Google Scholar
  14. Jonas, M., & Nilsson, S. (2001). The Austrian carbon database (ACDb) study — Overview. Interim Report IR-01-064. Laxenburg, Austria: International Institute for Applied Systems Analysis (IIASA).Google Scholar
  15. Jonas, M., & Nilsson, S. (2007). Prior to economic treatment of emissions and their uncertainties under the Kyoto protocol: scientific uncertainties that must be kept in mind. (This issue).Google Scholar
  16. Lim, B., Boileau, P., Bonduki, Y., van Amstel, A. R., Janssen, L. H. J. M., Olivier, J. G. J., et al. (1999). Improving the quality of national greenhouse gas inventories. Environmental Science & Policy, 2, 335–346.CrossRefGoogle Scholar
  17. Monni, S., Syri, S., Pipatti, R., & Savolainen, I. (2004a). Comparison of uncertainty in different emission trading schemes. In Proceedings of the workshop uncertainty in greenhouse gas inventories: Verification, compliance & trading (pp. 106–115). Warsaw, Poland: SRI PAS & IIASA. http://www.ibspan.waw.pl/GHGUncert2004/papers/Monni.pdf.Google Scholar
  18. Monni, S., Syri, S., & Savolainen, I. (2004b). Uncertainties in the finnish greenhouse gas emission inventory. Environmental Science & Policy, 7, 87–98.CrossRefGoogle Scholar
  19. Montgomery, W. D. (1972). Markets in licenses and efficient pollution control programs. Journal of Economic Theory, 5, 395–418.CrossRefGoogle Scholar
  20. Nahorski, Z., & Horabik, J. (2005). Fuzzy approximations in determining trading rules for highly uncertain emissions of pollutants. In P. Grzegorzewski, M. Krawczak & S. Zadrozny (Eds.), Issues in Soft Computing Theory and Applications (pp. 195–209), Warsaw, Poland: EXIT.Google Scholar
  21. Nahorski, Z., Horabik, J., & Jonas, M. (2004). Greenhouse gas emission uncertainty in compliance proving and emission trading. In Proceedings of the workshop uncertainty in greenhouse gas inventories: Verification, compliance & trading (pp. 116–125). Warsaw, Poland: SRI PAS & IIASA. http://www.ibspan.waw.pl/GHGUncert2004/papers/Nahorski.pdf.Google Scholar
  22. Nahorski, Z., & Jeda, W. (2002). Dynamics and uncertainty under Kyoto obligations. In IIASA/FOR Workshop ‘GHG Accounting: Uncertainty — Risk — Verification (pp. 13–14). Laxenburg: International Institute for Applied Systems Analysis (IIASA).Google Scholar
  23. Nahorski, Z., & Jeda, W. (2007). Processing National CO2 inventory emission data and their total uncertainty estimates. (This issue).Google Scholar
  24. Nahorski, Z., Jeda, W., Horabik, J., & Jonas, M. (2005). Propozycja zarzadzania niepewnościa bilansu gazów cieplarnianych w ramach protokołu z Kioto. In J. Kacprzyk, Z. Nahorski & D. Wagner (Eds.), Zastosowania badań systemowych w nauce, technice i ekonomii (pp. 357–372). Warsaw, Poland: EXIT.Google Scholar
  25. Nahorski, Z., Jeda, W., & Jonas, M. (2003). Coping with uncertainty in verification of the Kyoto obligations. In J. Studziński, L. Drelichowski & O. Hryniewicz (Eds.), Zastosowania informatyki i analizy systemowej w zarzadzaniu (pp. 305–317). Warsaw, Poland: SRI PAS.Google Scholar
  26. Nilsson, S., Shvidenko, A., Stolbovoi, V., Gluck, M., Jonas, M., & Obersteiner, M. (2000). Full carbon account for Russia. Interim Report IR-00-021. Laxenburg, Austria: International Institute for Applied Systems Analysis (IIASA). (Also featured in: New Scientist, 2253, 18–19, August 2000.)Google Scholar
  27. Nordhaus, W. D. (2005). Life after Kyoto: Alternative approaches to global warming policies. Working Paper 11889. Cambridge, MA: National Bureau of Economic Research. See http://www.nber.org/papers/w11889.Google Scholar
  28. Obersteiner, M., Ermoliev, Y., Gluck, M., Jonas, M., Nilsson, S., & Shvidenko, A. (2000). Avoiding a lemons market by including uncertainty in the Kyoto protocol: Same mechanism — Improved rules. Interim Report IR-00-043. Laxenburg, Austria: International Institute for Applied Systems Analysis (IIASA).Google Scholar
  29. Rypdal, K., & Winiwarter, W. (2001). Uncertainty in greenhouse gas emission inventories — Evaluation, comparability and implications. Environmental Science & Policy, 4, 104–116.Google Scholar
  30. Rypdal, K., & Zhang, L.-C. (2000). Uncertainties in the Norwegian greenhouse gas emission inventory. Report 2000/13. Oslo, Norway: Statistics Norway.Google Scholar
  31. Salway, A., Murrells, T., Milne, R., & Ellis, S. (2002). UK greenhouse gas inventory, 1990 to 2000: Annual report for submission under the framework convention on climate change. Didcot, UK: AEA Technology.Google Scholar
  32. Tietenberg, T. H. (1985). Emission trading, an exercise in reforming pollution policy. Washington DC: Resources for the Future Inc.Google Scholar
  33. van Amstel, A. R., Olivier, J. G. J., & Ruyssenaars, P. G. (Eds.) (2000). Monitoring of greenhouse gases in the Netherlands: uncertainties and priorities for improvement. Report 773201 003. Bilthoven, The Netherlands: National Institute of Public Health and the Environment.Google Scholar
  34. Victor, D. G. (1991). Limits of market-based strategies for slowing global warming: the case of tradable permits. Policy Sciences, 24, 199–222.CrossRefGoogle Scholar
  35. Vreuls, H. H. J. (2004). Uncertainty analysis of Dutch greenhouse gas emission data, a first qualitative and quantitative (TIER2) analysis. In Proceedings of the workshop uncertainty in greenhouse gas inventories: Verification, compliance & trading (pp. 34–44). Warsaw, Poland: SRI PAS & IIASA. http://www.ibspan.waw.pl/GHGUncert2004/papers/Vreuls.pdf.Google Scholar
  36. Winiwarter, W. (2007). National greenhouse gas inventories: understanding uncertainties versus potential for improving reliability. (This issue).Google Scholar
  37. Winiwarter, W., & Rypdal, K. (2001). Assessing the uncertainty associated with national greenhouse gas emission inventories: a case study for Austria. Atmospheric Environment, 35, 5425–5440.CrossRefGoogle Scholar

Copyright information

© Springer Science + Business Media B.V. 2007

Authors and Affiliations

  1. 1.Systems Research InstitutePolish Academy of SciencesWarsawPoland
  2. 2.International Institute for Applied Systems AnalysisLaxenburgAustria

Personalised recommendations